Improving on daily measures of price discovery

Detalhes bibliográficos
Autor(a) principal: Dias, Gustavo Fruet
Data de Publicação: 2017
Outros Autores: Fernandes, Marcelo, Scherrer, Cristina Mabel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional do FGV (FGV Repositório Digital)
Texto Completo: http://hdl.handle.net/10438/18017
Resumo: We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily VECM regressions as standard in the literature. We show that our estimator is not only consistent, but also outperforms the standard daily VECM in finite samples. We illustrate our theoretical findings by studying the price discovery process of 10 actively traded stocks in the U.S. from 2007 to 2013.
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spelling Dias, Gustavo FruetFernandes, MarceloScherrer, Cristina MabelEscolas::EESP2017-03-07T15:07:10Z2017-03-07T15:07:10Z2017TD 444http://hdl.handle.net/10438/18017We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily VECM regressions as standard in the literature. We show that our estimator is not only consistent, but also outperforms the standard daily VECM in finite samples. We illustrate our theoretical findings by studying the price discovery process of 10 actively traded stocks in the U.S. from 2007 to 2013.engEESP - Textos para Discussão;TD 444High-frequency dataPrice discoveryKernel regressionTime-varying coefficient modelsVECMEconomiaPreçosValor (Economia)Improving on daily measures of price discoveryinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlereponame:Repositório Institucional do FGV (FGV Repositório Digital)instname:Fundação Getulio Vargas (FGV)instacron:FGVinfo:eu-repo/semantics/openAccessTEXTTD 444 - Gustavo_Marcelo_Cristina.pdf.txtTD 444 - Gustavo_Marcelo_Cristina.pdf.txtExtracted texttext/plain38278https://repositorio.fgv.br/bitstreams/372275be-a4c1-49d5-b67f-db7ce731695b/downloadbd7682d9d89c26cc588c57e712133beaMD58ORIGINALTD 444 - Gustavo_Marcelo_Cristina.pdfTD 444 - 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dc.title.eng.fl_str_mv Improving on daily measures of price discovery
title Improving on daily measures of price discovery
spellingShingle Improving on daily measures of price discovery
Dias, Gustavo Fruet
High-frequency data
Price discovery
Kernel regression
Time-varying coefficient models
VECM
Economia
Preços
Valor (Economia)
title_short Improving on daily measures of price discovery
title_full Improving on daily measures of price discovery
title_fullStr Improving on daily measures of price discovery
title_full_unstemmed Improving on daily measures of price discovery
title_sort Improving on daily measures of price discovery
author Dias, Gustavo Fruet
author_facet Dias, Gustavo Fruet
Fernandes, Marcelo
Scherrer, Cristina Mabel
author_role author
author2 Fernandes, Marcelo
Scherrer, Cristina Mabel
author2_role author
author
dc.contributor.unidadefgv.por.fl_str_mv Escolas::EESP
dc.contributor.author.fl_str_mv Dias, Gustavo Fruet
Fernandes, Marcelo
Scherrer, Cristina Mabel
dc.subject.eng.fl_str_mv High-frequency data
Price discovery
Kernel regression
Time-varying coefficient models
VECM
topic High-frequency data
Price discovery
Kernel regression
Time-varying coefficient models
VECM
Economia
Preços
Valor (Economia)
dc.subject.area.por.fl_str_mv Economia
dc.subject.bibliodata.por.fl_str_mv Preços
Valor (Economia)
description We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily VECM regressions as standard in the literature. We show that our estimator is not only consistent, but also outperforms the standard daily VECM in finite samples. We illustrate our theoretical findings by studying the price discovery process of 10 actively traded stocks in the U.S. from 2007 to 2013.
publishDate 2017
dc.date.accessioned.fl_str_mv 2017-03-07T15:07:10Z
dc.date.available.fl_str_mv 2017-03-07T15:07:10Z
dc.date.issued.fl_str_mv 2017
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10438/18017
dc.identifier.sici.none.fl_str_mv TD 444
identifier_str_mv TD 444
url http://hdl.handle.net/10438/18017
dc.language.iso.fl_str_mv eng
language eng
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dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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